@@ -19,3 +19,31 @@ resources you have available.
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Please turn in an updated notebook with your strategy, as well as text in the
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notebook describing it and its performance.
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+
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+
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+ ## Part 2 - Play Pong
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+
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+ Implement an agent to play Pong - the OpenAI Gym
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+ [ integrates an Atari environment] ( https://github.com/openai/gym#atari ) , and you
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+ can start by trying
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+ [ example agents] ( https://github.com/openai/gym/tree/master/examples/agents ) . The
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+ random agent is a simple initial example, and the keyboard agent can allow you
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+ to actually play the game yourself (and potentially use that data to train
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+ some other agent). The example notebook from the first coding challenge has
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+ useful snippets of code for visualizing what is going on.
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+ After getting set up and playing with a few agents, check out
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+ [ this article] ( http://karpathy.github.io/2016/05/31/rl/ ) on using policy
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+ gradients to train a model to play Pong. Code your own agent based on this
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+ technique - [ this video] ( https://youtu.be/YOW8m2YGtRg ) illustrates the end
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+ result of such an agent.
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+
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+
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+ ## Part 3 - An environment of your choice
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+ OpenAI supports
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+ [ many interesting environments] ( https://github.com/openai/gym#environments ) -
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+ pick one, and start by trying to run existing agents and find prior work (as
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+ with Pong). Then take a shot at writing your own - this is open-ended, so have
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+ fun and explore something that interests you, but also chat and share what
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+ you're doing so people can collaborate and learn from one another.
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